Job recommending method

Abstract

The invention discloses a job recommending method, and belongs to the technical field of recommending systems. The job recommending method has the advantages that the Matthew effect is avoided, the problem of cold start is solved, and the populations are well utilized to realize personalized recommending. The job recommending method comprises the following steps of obtaining user data and job data; establishing a user preference vector space model and a job vector space model; according to the user preference vector space model and the job vector space model, calculating multi-domain scoring values based on contents, obtaining first scoring values of jobs, and sequencing, so as to obtain a job set; when one job is submitted and belongs to the job set, calculating the scoring valves of the corresponding job based on the similarity of user background information according to the user preference vector space model and the job data, and obtaining second scoring valves of the corresponding job; according to the first scoring valves and the second scoring valves, obtaining the mixed scoring valves of the corresponding job, and sequencing, so as to obtain a recommending list.

Description

technical field [0001] The present invention relates to the technical field of recommendation systems, in particular to a job recommendation method. Background technique [0002] The development of the Internet has gradually brought people from the era of information scarcity into the era of information overload, information and its transmission forms have become diversified, and users' demands for information have become more and more diversified and personalized. The recommendation system is a tool for connecting users and information. On the one hand, it helps users find valuable information, and on the other hand, it also allows the information to be displayed in front of users who are interested in it in a timely manner. Recommendation systems can be roughly divided into personalized recommendation and non-personalized recommendation. [0003] Personalized recommendation system, as the name suggests, is a recommendation system that provides users with personalized info...

AI Technical Summary

Problems solved by technology

[0005] Traditional job recommendation systems cannot use groups to achieve personalized recommendations while taking into account the Matthew effect or data sparse problems

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